CN102291817A - Group positioning method based on location measurement sample in mobile communication network - Google Patents
Group positioning method based on location measurement sample in mobile communication network Download PDFInfo
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Abstract
The invention relates to a group positioning method based on a location measurement sample in a mobile communication network, which comprises the steps that mobile terminals to be tested transmit pilot signals to base stations at first, the base stations obtain the signal time of arrival (TOA) and the signal receiving power W of each mobile terminal from received signals, and the two measurement data and the plane coordinates (x, y) of the locations of the mobile terminals to be tested form measurement data vectors (TOA, W (x, y)); and after each base station calculates the positioning location of each mobile terminal according to the received measurement data vector of each mobile terminal, in combination with the data of a spatial location codebook and a location measurement sample database, each base station transmits the positioning location information to the corresponding mobile terminal. The group positioning method based on the location measurement sample in the mobile communication network has the advantages that in combination with history measurement data in a cell and the measurement parameters of the current multiple mobile terminals, only one time of positioning calculation is required, the group positioning demands of multiple users can be satisfied, the positioning accuracy is high, the measurement data can be obtained very easily and conveniently and the method is suitable for all kinds of existing mobile communication systems.
Description
Technical field
The present invention relates to the location technology in a kind of mobile communications network, exactly, relate to the position measurement sample that utilizes a plurality of portable terminals in a kind of mobile communications network and carry out the accurately method of group location, belong to the mobile communication technology field.
Background technology
Along with developing rapidly of mobile communication, the mobile location service of carrying out in the mobile communication system also more and more is subjected to numerous users' concern and application.Now, Chang Yong location method has following three kinds:
(1) based on time measurement, be the localization method of the TOA time of advent (Time Of Arrival) or time of advent difference TDOA (Time Difference Of Arrival): by detect the propagation time that radio wave receives from the base station to the portable terminal, calculate both distances, again by calculating the estimated position of portable terminal someway.Its positioning accuracy depends on the timing accuracy of communication system, and necessary strict synchronism between each base station, can not cause obvious influence to positioning result with the timing error of guaranteeing communication system itself.For example, application number is that 200780051228.1 Chinese patent application is just introduced the detailed process that a kind of method that adopts the Passive Positioning target in TOA or TDOA pattern is implemented the space piece at gridding (segmentation) locating area place, pass through iterative analysis again, form the piece collection of this network.During each iteration, all each piece of being correlated with to be subdivided into littler same sub-block, define affiliated locating area thereby increase accuracy.
(2) arrive the localization method of angle AOA (Angle Of Arrival) based on signal: detect the AOA of travelling carriage emission electric wave earlier by the base station receiving antenna array, be used to constitute the radially line from the base station to the travelling carriage, i.e. a rhumb line; Each AOA that utilizes a plurality of base stations to provide again measures numerical value, many rhumb line of can drawing, and its intersection point is exactly the estimated position of travelling carriage.Its advantage is that the location just can be realized in two base stations; But will there be receiving antenna array the base station, and the influence that its precision is subjected to channel is bigger, and in building close quarters location difficulty, can't realize in the GSM network.
(3) AGPS localization method: be a kind of base station information of comprehensive mobile communications network and the technology that GPS information positions travelling carriage.This method is: the GPS supplementary that travelling carriage utilizes communication network to provide receives the GPS primary signal, again the GPS primary signal is carried out demodulation and obtain GPS pseudorange information, mobile communications network is finished the information processing to GPS according to the supplementary of pseudorange information and other positioning equipment, and then estimates the position of this travelling carriage.In order to satisfy the positioning requirements of this method, at least to receive the signal of 4 satellites, but between the intensive high building in urban district, at interior of building or can only see any area that is less than 4 satellites, gps system is inoperative usually, so just can't carry out accurate location.And this method requires terminal to have the GPS receiver module, location cost height.
Above-mentioned three kinds of traditional localization methods all are at a specific terminal, and its location Calculation also has only a terminal to participate in.How to make full use of the measurement data of the numerous portable terminals in the network, can either improve positioning accuracy, can realize the group location of a plurality of portable terminals again fast under the universal mobile communications network, expediently; Yet the report of relevant this respect is still blank so far both at home and abroad.Therefore, this problem also just becomes the focus of scientific and technical personnel's concern in the industry.
Summary of the invention
In view of this, the group's localization method that the purpose of this invention is to provide the position-based measurement sample in a kind of mobile communications network, the present invention can make full use of the measurement data of numerous terminals in the network, improve positioning accuracy, can solve the group location of a plurality of portable terminals under the mobile communications network again fast, expediently simultaneously.
In order to reach the foregoing invention purpose, the invention provides group's localization method of the position-based measurement sample in a kind of mobile communications network, be based on the localization method that network measure is carried out; It is characterized in that: portable terminal to be measured is earlier to the base station pilot signal transmitted, the base station obtains time of arrival (toa) TOA (Time Of Arrival), the signal received power W of each portable terminal from received signal, and by the plane coordinates (x of these two measurement data and this portable terminal to be measured position, y) form measurement data vector (TOA, W, (x, y)); Each base station is according to the measurement data vector of its each portable terminal that the receives related data in conjunction with locus code book and position measurement sample storehouse, after calculating the position location of each portable terminal respectively, by each base station this positioning position information is sent to the corresponding mobile terminal respectively again.
The main innovation key technology of group's localization method of the present invention has following 4 points:
The one, the present invention proposes the initial method based on the terminal data vector in the locus code book of cluster and the position measurement sample storehouse, utilize the data vector in the position measurement sample storehouse of real-time update to upgrade the locus code book again, adopt the method for cluster can adapt to effectively in the sub-district in the practical communication, the present situation of the uneven distribution of communication focus has also made full use of the metrical information of each portable terminal in the sub-district.
The 2nd, be different from traditional localization method, the present invention is a kind of group's localization method of a plurality of terminals of effective realization based on sum-product algorithm: the present invention has adopted the measurement data of a plurality of portable terminals in the network, upgrade by mutual iteration, make full use of the metrical information of each portable terminal in the network, can either one-time positioning calculate the location estimation position that just can access a plurality of terminals, finish the group location; Also obviously improved the positioning accuracy of each terminal.
The 3rd, the present invention proposes based on position codebook searching method between the cell null of Euclidean distance, and the signal that has effectively merged in the code book of locus reaches time T OA and received signal power W information, reduces amount of calculation.
The 4th, when the quantity of terminal to be measured in the network was rare, the present invention proposed a kind ofly to adopt the data vector in the position measurement sample storehouse to assist the location as virtual terminal, thereby effectively assists terminal to be measured to realize the location, and guarantees positioning accuracy.
In a word, the advantage of the inventive method is: in conjunction with the measurement parameter of the historical measurement data in the sub-district and current a plurality of portable terminals, adopt the mode of group location, finishing one-time positioning calculates, just can satisfy numerous users' location requirement, and positioning accuracy is higher.Moreover the acquisition of needed measurement data is very easy, convenient, and (as GSM, CDMA, 3G etc.) are all applicable for existing various mobile communication system, so have good popularization and application prospect.
Description of drawings
Fig. 1 is the base station in the inventive method and the mutual schematic diagram of terminal to be measured.
Fig. 2 is group's localization method flow chart that the position-based in the mobile communications network of the present invention is measured sample.
Fig. 3 is the initialization locus code book flow chart in the inventive method.
Fig. 4 is that the sum-product algorithm in the inventive method is estimated terminal location flow chart to be measured.
Fig. 5 is that sum-product algorithm of the present invention is estimated terminal location principle schematic to be measured.
Fig. 6 is that a plurality of virtual terminals in the inventive method participate in iteration estimation principles schematic diagram.
Fig. 7 is that schematic diagram is upgraded in the position measurement sample storehouse among the present invention.
Fig. 8 is that the locus code book among the present invention upgrades flow chart.
Fig. 9 is that schematic diagram is divided in the emulation sub-district in the embodiment of the invention.
Figure 10 is two kinds of position root-mean-square error curve synoptic diagrams in the embodiment of the invention.
Embodiment
For making the purpose, technical solutions and advantages of the present invention clearer, the present invention is described in further detail below in conjunction with drawings and Examples.
The present invention is group's localization method that the position-based in a kind of mobile communications network of side Network Based is measured sample: earlier by portable terminal to be measured to the base station pilot signal transmitted, the metrical information that the base station draws portable terminal from the signal that receives (for example, can picked up signal in the GSM network reach time T OA (Time Of Arrival) and signal received power W), and by the plane coordinates (x of these two measurement data and this portable terminal to be measured position, y) form measurement data vector (TOA, W, (x, y)); Each base station is according to the measurement data vector of its each portable terminal that the receives related data in conjunction with locus code book and position measurement sample storehouse, after calculating the position location of each portable terminal respectively, by each base station this positioning position information is sent to the corresponding mobile terminal respectively again.As shown in Figure 1, three base station BSs
1, BS
2, BS
3Can both obtain three mobile terminal UE to be measured
1, UE
2, UE
3TOA and W measured value, the base station is carried out computing according to a little measurement data according to group's localization method of the present invention, draw the positioning result of each terminal after, send to terminal by the base station again.
UE among Fig. 1
4, UE
5It is the virtual terminal that relates in the inventive method.Because of in some special scenes, terminal to be measured in the subzone network may have only one or quantity few, when causing the inventive method effectively to carry out, the data vector that can choose several storages from the terminal database to be measured in position measurement sample storehouse and/or drive test terminal database is as the virtual terminal data vector in the network, and auxiliary terminal to be measured positions.When virtual terminal participation location estimation of the present invention was calculated, its initial position was estimated
Be exactly the plane coordinates in the data vector of storing, natural number subscript v is the virtual terminal sequence number.Calculate between any one virtual terminal and other terminals to be measured and/or the virtual terminal apart from the time, adopt earlier TOA in this virtual terminal data vector
vAnd W
vObtain the rough coordinates of this virtual terminal by least square method after, directly calculating just can obtain again.The back can specify it in step 2.
Referring to Fig. 2, introduce three concrete operations steps of the inventive method:
Terminal data vector among Fig. 2 is the basic processing unit of the inventive method, data in each terminal data vector have three: (TOA, W, (x, y)), wherein, (x, y) be the plane coordinates of this terminal location, TOA and W are respectively that this terminal sends to the power that each signal of base station time of advent and base station receive this signal.If there be n base station to participate in measuring, then in the data vector to there being n to organize the measured parameter value of TOA and W.
Referring to Fig. 3, the base station of introducing in this step 1 utilizes clustering method that drive test terminal data vector is carried out cluster, sets up initialized following content of operation by the vectorial locus code book of forming of cluster point data:
(11), several plane coordinatess are set in the sub-district are according to the geographical environment of sub-district
The cluster point, in the formula, natural number subscript c is the sequence number of cluster point, its maximum M
cBe cluster point sum; Subscript t is the cluster iterations, and initial value is 0;
(12) respectively each drive test terminal data vector is sought and the nearest cluster point in its plane coordinates position, and it is belonged to this cluster point; The drive test terminal data vector that will belong to same cluster point again forms a cluster group, makes each cluster point all corresponding with a cluster faciation;
(13) calculate the average of each cluster group plane coordinates respectively, as the cluster point after this cluster iteration
(14) calculate according to following formula and the square mean error amount E that judges cluster point plane coordinates after this cluster iteration and the cluster point plane coordinates before its iteration whether less than setting threshold:
If then cluster is finished, and define this cluster point plane coordinates and be
Otherwise, return execution in step (12);
(15) according to the plane coordinates (x of dissemination channel model and this cluster point
c, y
c), calculate the time of arrival (toa) of this cluster point
With received signal power W
c=W
Tx-L
c, and with this cluster point data vector (TOA
c, W
c, (x
c, y
c)) form be stored in the locus code book; In the formula, (x
n, y
n) for sequence number is the base station plane coordinates of n, V is the light velocity, W
TxFor the terminal signaling transmitted power and be fixed value, L
cBe the propagation path loss between this cluster point and base station, this propagation path loss numerical value is the propagation model according to practical application, utilizes distance calculation between base station and this cluster point to obtain.
For position measurement sample storehouse, its function is to go up limited nearest terminal data vector memory time, comprises the data vector of drive test terminal and terminal to be measured.Its memory space is divided into two parts: drive test terminal database and terminal database to be measured, corresponding stored drive test terminal data vector sum terminal data vector to be measured respectively.Because it is empty also not having terminal data vector to be measured, terminal database then to be measured during initialization, the drive test terminal database then can be chosen several drive test terminal data vectors and be stored in wherein.
This step 2 comprises following content of operation:
(21) initial position of estimation terminal to be measured: elder generation is with the TOA of each terminal to be measured
eAnd W
eValue is parameter, in the code book of locus, searches and the immediate cluster point data vector of this terminal data vector to be measured, and with the initial position estimated value of the plane coordinates in this cluster point data vector as terminal to be measured
For the virtual terminal of assist location, then with the plan position approach coordinate in its data vector as the initial position estimated value
Wherein, subscript e and v are respectively terminal serial number to be measured and virtual terminal sequence number.
The concrete operations of this step (21) the contents are as follows described:
(211) to each terminal to be measured in the sub-district, with its data vector (TOA
e, W
e, (x
e, y
e)) in TOA
eAnd W
eBeing parameter, is benchmark with equivalent Euclidean distance, searches cluster point data vector (TOA immediate with it in the code book of locus
c, W
c, (x
c, y
c)); Can't directly calculate because of TOA is different with the W dimension, so earlier unified dimension: TOA and W are converted to long measure, according to signal propagation model, respectively by W
eAnd TOA
eCalculate the estimated distance of terminal to be measured and base station
With
Similarly, also in the code book of locus, calculate the estimated distance of cluster point and base station
With
(212) according to equivalent Euclidean distance computing formula:
In the code book of locus, seek equivalent Euclidean distance minimal data vector with terminal data vector to be measured; In the formula, α is a weight coefficient, is used for the measurement accuracy different errors that cause of equilibrium because of the TOA and the W of actual measurement, and W measured value error is bigger usually, and the numerical value of α depends on actual conditions;
(213) traversal locus code book is chosen wherein equivalent Euclidean distance ε
E, cPosition coordinates (x in the minimum cluster point data vector
c, y
c) as the initial position estimated value of terminal to be measured
Initial position estimated value for the virtual terminal of assist location
It then is the plan position approach coordinate in its data vector.
(22) the approximate distance initial value of any two terminal rooms of calculating: according to time of arrival (toa) TOA and the signal received power W in each terminal data vector sum virtual terminal data vector to be measured, adopt least square method to obtain the rough coordinates of each terminal to be measured and virtual terminal, and then calculate the approximate distance initial value between any two terminals in the whole terminals that comprise terminal to be measured and virtual terminal.
The concrete operations of this step (22) the contents are as follows described:
(221) to each terminal in the whole terminals that comprise terminal to be measured and virtual terminal, be the TOA and the W of certain base station correspondence of n according to sequence number in its data vector respectively, list its distance calculation formula:
In the formula, (x
n, y
n) be this base station plane coordinates, the natural number subscript n is the base station sequence number; α is a weight coefficient,
Be respectively by the pairing TOA of base station n and this terminal of W calculating and the distance of base station n;
(222), be respectively provided to few 3 above-mentioned distance calculation formula, and, calculate the rough coordinates of each terminal that comprises terminal to be measured and virtual terminal with least square method as simultaneous equations at the base station of different sequence numbers
(223) according to the rough coordinates of each terminal, directly calculate the approximate distance initial value between any two terminals in the whole terminals that comprise terminal to be measured and virtual terminal
In the formula, natural number subscript i and j are respectively the sequence number of two different terminals in all terminals that comprise terminal to be measured and virtual terminal, and natural number subscript k is the iterative computation number of times in the subsequent step, and initial value k=0 represents not iteration.
(23) adopt sum-product algorithm to calculate the final position estimated value of terminal to be measured: the position distribution of supposing each terminal to be measured and virtual terminal all is to obtain the two-dimentional Gaussian Profile that the initial position estimated value is the center with step (21), approximate distance initial value in the whole terminals that comprise terminal to be measured and virtual terminal that integrating step (22) obtains again between any two terminals, after adopting the sum-product algorithm iteration repeatedly then, obtain the final position estimated value of each terminal to be measured; And the final position estimated value is sent to each terminal to be measured by the base station.
The concrete operations of this step (23) the contents are as follows described (referring to the flow process of Fig. 4 and the schematic diagram of Fig. 5):
(231) because of the initial position distribution probability P of each terminal to be measured and virtual terminal
i(x is to be the two-dimentional Gaussian Profile at center with the initial position estimated value that step (21) obtains y), and its variance depends on substantial measurement errors; So the initialization setting comprises each terminal UE of terminal to be measured and virtual terminal
iThe position distribution probability
In the formula, natural number subscript i is a terminal serial number, and terminal serial number scope to be measured is [1, M], and the virtual terminal serial number range is [M+1, N], and promptly the i maximum is N;
(232) for each terminal UE
iWith another terminal UE
j, carry out following iterative operation: with another terminal UE after the k-1 time iteration
jThe position distribution probability
Be benchmark, according to these two terminal UE after the k-1 time iteration
iWith UE
jBetween approximate distance
Calculate another terminal UE
jBe positioned at coordinate (x
j, y
j) time, terminal UE
iThe position distribution probability
These two terminal UE
iWith UE
jBetween approximate distance
Gaussian distributed, approximate distance
Average be UE
iWith UE
jCoordinate (x
i, y
i) and (x
j, y
j) between distance, its variance depends on the substantial measurement errors of TOA and W;
According to another terminal UE
jCoordinate (x
j, y
j) be arranged in the diverse location of sub-district, calculate this terminal UE respectively
iThe diverse location distribution probability, again terminal UE
iAbove-mentioned all position distribution probability numbers sum that adds up, during as the k time iteration, another terminal UE
jTo terminal UE
iThe correction value of position distribution probability
(233) each terminal UE
iAll with its initial position coordinate P
i(x
i, y
i) with every other terminal to the correction value of its position distribution probability
Tire out and take advantage of amassing, as the position distribution probability after its k time iteration
Simultaneously, terminal UE
iAlso with the correction value of every other terminal to its position distribution probability
Tire out take advantage of long-pending, as after the k time iteration, terminal UE
iThe aided location distribution probability
(234) calculate each terminal UE earlier
iThe desired value of plane coordinates under the aided location distribution probability, i.e. the average of its a plurality of plane coordinatess, obtain the k time iteration after, this terminal UE
iPosition coordinates
And then after directly calculating the k time iteration, the approximate distance of each terminal room
Judge simultaneously whether iterations k reaches set point number, if then carry out subsequent step (235); Otherwise, return execution in step (232);
(235) each terminal UE to be measured
iThe final position distribution probability
Calculate this terminal location coordinate to be measured at final position distribution probability P '
i(x
i, y
i) under desired value, promptly the average of its a plurality of plane coordinatess is exactly the final position estimated value of this terminal to be measured
(236) base station is with each terminal UE to be measured
iThe final position estimated value send to each terminal to be measured.
Among Fig. 5, P
iBe any one terminal UE
iThe initial position distribution probability,
Be the k time UE after the iterative computation
iThe position distribution probability,
When being the k time iteration, terminal UE
iAt existing position distribution probability
Down, after the k-1 time iteration that calculates according to the base station with another terminal UE
jApproximate distance
To another terminal UE
jThe correction value of position distribution probability.During each iteration, for any one terminal UE
i, calculate the correction value of other-end, again with terminal UE to its position distribution probability
iInitial position distribution probability P
iTired taking advantage of obtains terminal UE after this time iteration
iThe position distribution probability.So behind the iteration several times, can make full use of the terminal metrical information that all participate in calculating, obtain terminal UE to be measured
iFinal position estimated value more accurately, thus reach the purpose of group location.
The description of front has utilized some virtual terminals in the position measurement sample storehouse, and each virtual terminal has all participated in all iterative computation.In order to make full use of the data message of position measurement sample library storage, can do following improvement to above-mentioned handling process: make each iterative computation all participate in (as shown in Figure 6) by different virtual terminals, for example, assumed position is measured in the sample storehouse and is stored 100 data vectors, during each iteration, therefrom choose 10 and participate in iterative computation as virtual terminal; Next time, iteration was then chosen other 10, so only needed iterative computation 10 times, just can use 100 all in position measurement sample storehouse data vectors, under the situation that does not improve computation complexity, had maximally utilised available data information.
This step 3 comprises following concrete operations content:
(31) produce new terminal data vector to be measured or drive test terminal data vector in the network, just begin to upgrade position measurement sample storehouse: if in the position measurement sample storehouse memory space of terminal database to be measured less than, just store with terminal data vector to be measured that should be new is direct; Otherwise, in the alternative terminal database to be measured of terminal data vector to be measured that just will be new memory time data vector at most; The update method of drive test terminal data vector is identical with terminal data vector to be measured, makes limited terminal to be measured and the drive test terminal data vector (referring to shown in Figure 7) that the time that stores all the time in the position measurement sample storehouse is nearest like this;
From Fig. 7, can see: the update cycle T of terminal database to be measured
eUpdate cycle T with the drive test terminal database
lBe different, and depend on concrete actual conditions.Generally, because the measurement of terminal to be measured is more frequent, its update cycle is shorter; For the drive test terminal database, often because the variation of geographical environment in the sub-district (as newly constructed house etc.), need carry out actual drive test ability once more to its renewal, so the update cycle is longer.
(32) after the renewal in sample storehouse is measured in the completing place, just,, finish the renewal of locus code book by clustering method according to drive test terminal and terminal data vector to be measured in the position measurement sample storehouse after upgrading.This step (32) comprises following concrete operations content (referring to shown in Figure 8):
(321) data vector that will upgrade in the preceding locus code book is put initial value as cluster;
(322), calculate the cluster point of Euclidean distance minimum equivalent respectively, and it is belonged to this cluster point with it to each the drive test terminal in the position measurement sample storehouse and the data vector of terminal to be measured; Feasible cluster group of data vector formation who belongs to the terminal to be measured and the drive test terminal of same cluster point, promptly each cluster point is all corresponding with a cluster faciation; Each data volume outline when calculating equivalent Euclidean distance is unified;
(323) calculate the average of every measurement data of the data vector of terminal to be measured among each cluster group and drive test terminal, obtain the cluster point after this cluster iteration;
(324) calculate and the mean square error of judging the cluster point before cluster point and its cluster iteration after this cluster iteration whether less than setting threshold, if, then deposit this cluster point data vector in the locus code book, finish the renewal of locus code book; Otherwise, return execution in step (322).
The present invention has carried out repeatedly embodiment emulation experiment and simulation, the network cell layout of the inventive method emulation is shown in the cellular cell cell 0 among Fig. 9, this radius of society is 1km, the center is provided with 1 base station, and coordinate is (0,0), the sub-district is divided into 96 little equilateral triangles, each little equilateral triangle center is set to the cluster point, like this, has 96 cluster points.The measured value of TOA among the emulation embodiment and received signal power W is respectively with cell 0, and the base station of cell 5 and cell 6 is that benchmark carries out simulation test and obtains.
30 points of picked at random in sub-district cell 0, its plane coordinates obedience variance is 5000 two-dimentional Gaussian Profile, and wherein the two-dimentional Gaussian Profile center of 15 points is (50,100), and the two-dimentional Gaussian Profile center of all the other 15 points is (50,80).20 of picked at random are terminal to be measured from 30 points again, other 10 as virtual terminal.
In order to simulate the drive test terminal data vector in the real network, 798 drive test sampled points of random distribution in the cell 0 of this sub-district, it is 5000 two-dimentional Gaussian Profile that these drive test sampled points are all obeyed variance, distribution center is respectively (50,100), (50,80), (40 ,-90) and (45 ,-105).
In the mobile communications network of reality, because influences such as multipath in the communication environments and shadow fading, all can there be certain error in the base station to the measurement data TOA and the W of portable terminal, thereby also all there is error in the distance that causes calculating terminal and base station with angle:
In the formula, V is the light velocity 3 * 10
8M, d be between terminal and the base station apart from true value, TOA is the time of arrival (toa) measured value, n
TOABe measure error, W is the received signal power measurement value, W
TxFor sending signal power, C is parameters such as antenna height, is fixed value in special scenes, n
WThe measure error that causes for factors such as multipath and shadow fadings.
For simulating these errors, TOA in the emulation and the measure error n of W
TOAAnd n
WObey respectively
Gaussian Profile.Introduce the emulation testing result of embodiment below:
Emulation one: (σ
TOA, σ
W) value is (2.67ns, 3.163dB) time, the terminal root-mean-square error curve to be measured that emulation is 100 times as shown in figure 10, for positioning result is compared, under identical simulated conditions, also adopt traditional TOA localization method (least square method) to carry out emulation testing.
As can be seen from Fig. 10, localization method of the present invention is compared with traditional TOA localization method: positioning accuracy obviously improves, after the iterative computation 5 times, terminal positioning result's to be measured root-mean-square error is about 102m, and the about 128m of the root-mean-square error of TOA localization method under the similarity condition.In addition, iteration about 3 times, the error curve of localization method of the present invention just tends towards stability.
Can see by above-mentioned simulation result, group's location technology of the position-based test sample book in the mobile communications network of the present invention is feasible, by utilizing locus code book and position measurement sample storehouse, in conjunction with current a plurality of terminal measurement data, can make full use of the metrical information of base station, obtain positioning performance preferably terminal.And the used data of the inventive method only are TOA and two measurement data of received signal power, are easy to obtain, and are all applicable in the mobile communications network of existing uses such as GSM.
The above only is preferred embodiment of the present invention, and is in order to restriction the present invention, within the spirit and principles in the present invention not all, any modification of being made, is equal to replacement, improvement etc., all should be included within the scope of protection of the invention.
Claims (10)
1. the position-based in the mobile communications network is measured group's localization method of sample, is based on the localization method that network measure is carried out; It is characterized in that: portable terminal to be measured is earlier to the base station pilot signal transmitted, the base station obtains time of arrival (toa) TOA, the signal received power W of each portable terminal from received signal, and by the plane coordinates (x of these two measurement data and this portable terminal to be measured position, y) form measurement data vector (TOA, W, (x, y)); Each base station is according to the measurement data vector of its each portable terminal that the receives related data in conjunction with locus code book and position measurement sample storehouse, after calculating the position location of each portable terminal respectively, by each base station this positioning position information is sent to the corresponding mobile terminal respectively again.
2. method according to claim 1 is characterized in that: accompanying method comprises following operating procedure:
(1) initialization is provided with locus code book and position measurement sample storehouse: when building and safeguard the sub-district, following three data are surveyed in the setting place in the sub-district earlier: the signal that is positioned at the drive test terminal transmission of this position arrives base station time T OA
l, the base station receives the power W of this signal
lPlane coordinates (x with this position
l, y
l), wherein natural number subscript l is the drive test position number, and above-mentioned three data are constituted drive test terminal data vector (TOA
l, W
l, (x
l, y
l)); After the base station utilizes clustering method that these drive test terminal data vectors are carried out clustering processing, set up the initialization locus code book of forming by cluster point data vector; Because of position measurement sample storehouse last nearest limited the terminal data vector that comprises drive test terminal and terminal to be measured of a memory time, and also do not have terminal data vector to be measured this moment, is stored in position measurement sample storehouse so choose the alternative terminal data vector to be measured of several drive test terminal data vectors;
(2) estimate terminal location to be measured: when having terminal to be measured to initiate Location Request in the network, each base station is calculated this terminal signaling to be measured according to the terminal signaling to be measured that receives and is arrived base station time T OA
eReceived power W with this signal
e, and with the plane coordinates (x of these two measurement data with this terminal to be measured
e, y
e) formation terminal data vector (TOA to be measured
e, W
e, (x
e, y
e)), wherein natural number subscript e is a terminal serial number to be measured; Therefore this terminal plane coordinates (x to be measured the time
e, y
e) the unknown, so initialization is provided with its plane coordinates (x
e, y
e) be this center of housing estate position; Then, with TOA
eAnd W
eTwo measurement data are parameter, in the code book of locus, search and the immediate cluster point data vector of this terminal data vector to be measured, and with the initial position estimated value of the plane coordinates in this cluster point data vector as this terminal to be measured
Again according to the TOA in the terminal data vector to be measured
eAnd W
e, adopt least square method to calculate the rough coordinates of each terminal to be measured
And then obtain approximate distance initial value between each terminal to be measured; Then, the initial position distribution probability of supposing terminal to be measured is with its initial position estimated value
Be the two-dimentional Gaussian Profile at center,, adopt repeatedly the sum-product algorithm of iteration, calculate the final position estimated value of terminal to be measured in conjunction with the approximate distance initial value between each terminal to be measured
At last, the base station sends to each terminal to be measured with the final position estimated value;
(3) real-time update locus code book and position measurement sample storehouse: because of the renewal of terminal database to be measured in the position measurement sample storehouse and drive test terminal database independently of one another, so in the time of will storing new terminal data vector to be measured or drive test terminal data vector, all be to replace separately time data vector at most in the database respectively, finish Data Update; Then, drive test terminal and terminal data vector to be measured in the position measurement sample storehouse after adopt upgrading carry out cluster again, obtain new cluster point after, again that new cluster point is corresponding data vector deposits the locus code book in, finishes the renewal of locus code book.
3. method according to claim 2, it is characterized in that: in the described step (1), the base station utilizes clustering method that drive test terminal data vector is carried out clustering processing, sets up initialized operation by the vectorial locus code book of forming of cluster point data and comprises following content:
(11), several plane coordinatess are set in the sub-district are according to the geographical environment of sub-district
The cluster point, in the formula, natural number subscript c is the sequence number of cluster point, its maximum M
cBe cluster point sum; Subscript t is the cluster iterations, and initial value is 0;
(12) respectively each drive test terminal data vector is sought and the nearest cluster point in its plane coordinates position, and it is belonged to this cluster point; The drive test terminal data vector that will belong to same cluster point again forms a cluster group, makes each cluster point all corresponding with a cluster faciation;
(13) calculate the average of each cluster group plane coordinates respectively, as the cluster point after this cluster iteration
(14) calculate according to following formula and the square mean error amount E that judges cluster point plane coordinates after this cluster iteration and the cluster point plane coordinates before its iteration whether less than setting threshold:
If then cluster is finished, and define this cluster point plane coordinates and be
Otherwise, return execution in step (12);
(15) according to the plane coordinates (x of dissemination channel model and this cluster point
c, y
c), calculate the time of arrival (toa) of this cluster point
With received signal power W
c=W
Tx-L
c, and with this cluster point data vector (TOA
c, W
c, (x
c, y
c)) form be stored in the locus code book; In the formula, (x
n, y
n) for sequence number is the base station plane coordinates of n, V is the light velocity, W
TxFor the terminal signaling transmitted power and be fixed value, L
cBe the propagation path loss between this cluster point and base station, this propagation path loss numerical value is the propagation model according to practical application, utilizes distance calculation between base station and this cluster point to obtain.
4. method according to claim 2, it is characterized in that: in the described step (2), in the sub-district, have only one or quantity terminal to be measured seldom, when causing very little effectively carrying out this this localization method because of terminal quantity to be measured, just the data vector of choosing several storages respectively from the terminal database to be measured and/or the drive test terminal database in position measurement sample storehouse is as the virtual terminal the network, participates in and auxiliary terminal to be measured is carried out location positioning; The initial position estimated value of these virtual terminals
Be the plane coordinates in the data vector of storing, wherein natural number subscript v is the virtual terminal sequence number; Calculate between the virtual terminal or the approximate distance initial value of itself and terminal to be measured is TOA and the W numerical value that utilizes earlier in the data vector of this storage, calculate the rough coordinates of each virtual terminal by least square method
After, directly calculate distance between the two again.
5. method according to claim 2 is characterized in that: described step (2) comprises following content of operation:
(21) initial position of estimation terminal to be measured: elder generation is with the TOA of each terminal to be measured
eAnd W
eValue is parameter, in the code book of locus, searches and the immediate cluster point data vector of this terminal data vector to be measured, and with the initial position estimated value of the plane coordinates in this cluster point data vector as terminal to be measured
For the virtual terminal of assist location, then with the plan position approach coordinate in its data vector as the initial position estimated value
Wherein, subscript e and v are respectively terminal serial number to be measured and virtual terminal sequence number;
(22) the approximate distance initial value of any two terminal rooms of calculating: according to time of arrival (toa) TOA and the signal received power W in each terminal data vector sum virtual terminal data vector to be measured, adopt least square method to obtain the rough coordinates of each terminal to be measured and virtual terminal, and then calculate the approximate distance initial value between any two terminals in the whole terminals that comprise terminal to be measured and virtual terminal;
(23) adopt sum-product algorithm to calculate the final position estimated value of terminal to be measured: the position distribution of supposing each terminal to be measured and virtual terminal all is to obtain the two-dimentional Gaussian Profile that the initial position estimated value is the center with step (21), approximate distance initial value in the whole terminals that comprise terminal to be measured and virtual terminal that integrating step (22) obtains again between any two terminals, after adopting the sum-product algorithm iteration repeatedly then, obtain the final position estimated value of each terminal to be measured; And the final position estimated value is sent to each terminal to be measured by the base station.
6. method according to claim 5 is characterized in that: described step (21) comprises following concrete operations content:
(211) to each terminal to be measured in the sub-district, with its data vector (TOA
e, W
e, (x
e, y
e)) in TOA
eAnd W
eBeing parameter, is benchmark with equivalent Euclidean distance, searches cluster point data vector (TOA immediate with it in the code book of locus
c, W
c, (x
c, y
c)); Can't directly calculate because of TOA is different with the W dimension, so earlier unified dimension: TOA and W are converted to long measure, according to signal propagation model, respectively by W
eAnd TOA
eCalculate the estimated distance of terminal to be measured and base station
With
Similarly, also in the code book of locus, calculate the estimated distance of cluster point and base station
With
(212) according to equivalent Euclidean distance computing formula:
In the code book of locus, seek equivalent Euclidean distance minimal data vector with terminal data vector to be measured; In the formula, α is a weight coefficient, is used for the measurement accuracy different errors that cause of equilibrium because of the TOA and the W of actual measurement, and the numerical value of α depends on actual conditions;
(213) traversal locus code book is chosen wherein equivalent Euclidean distance ε
E, cPosition coordinates (x in the minimum cluster point data vector
c, y
c) as the initial position estimated value of terminal to be measured
The initial position estimated value of the virtual terminal of assist location wherein
Be the plan position approach coordinate in its data vector.
7. method according to claim 5 is characterized in that: described step (22) comprises following concrete operations content:
(221) to each terminal in the whole terminals that comprise terminal to be measured and virtual terminal, be the TOA and the W of certain base station correspondence of n according to sequence number in its data vector respectively, list its distance calculation formula:
In the formula, (x
n, y
n) be this base station plane coordinates, the natural number subscript n is the base station sequence number; α is a weight coefficient,
Be respectively by the pairing TOA of base station n and this terminal of W calculating and the distance of base station n;
(222), be respectively provided to few 3 above-mentioned distance calculation formula, and, calculate the rough coordinates of each terminal that comprises terminal to be measured and virtual terminal with least square method as simultaneous equations at the base station of different sequence numbers
(223) according to the rough coordinates of each terminal, directly calculate the approximate distance initial value between any two terminals in the whole terminals that comprise terminal to be measured and virtual terminal
In the formula, natural number subscript i and j are respectively the sequence number of two different terminals in all terminals that comprise terminal to be measured and virtual terminal, and natural number subscript k is the iterative computation number of times in the subsequent step, and initial value k=0 represents not iteration.
8. according to claim 5 or 7 described methods, it is characterized in that: described step (23) comprises following concrete operations content:
(231) because of the initial position distribution probability P of each terminal to be measured and virtual terminal
i(x is to be the two-dimentional Gaussian Profile at center with the initial position estimated value that step (21) obtains y), and its variance depends on substantial measurement errors; So the initialization setting comprises each terminal UE of terminal to be measured and virtual terminal
iThe position distribution probability
In the formula, natural number subscript i is a terminal serial number, and terminal serial number scope to be measured is [1, M], and the virtual terminal serial number range is [M+1, N], and promptly the i maximum is N;
(232) for each terminal UE
iWith another terminal UE
j, carry out following iterative operation: with another terminal UE after the k-1 time iteration
jThe position distribution probability
Be benchmark, according to these two terminal UE after the k-1 time iteration
iWith UE
jBetween approximate distance
Calculate another terminal UE
jBe positioned at coordinate (x
j, y
j) time, terminal UE
iThe position distribution probability
These two terminal UE
iWith UE
jBetween approximate distance
Gaussian distributed, approximate distance
Average be UE
iWith UE
jCoordinate (x
i, y
i) and (x
j, y
j) between distance, its variance depends on the substantial measurement errors of TOA and W;
According to another terminal UE
jCoordinate (x
j, y
j) be arranged in the diverse location of sub-district, calculate this terminal UE respectively
iThe diverse location distribution probability, again terminal UE
iAbove-mentioned all position distribution probability numbers sum that adds up, during as the k time iteration, another terminal UE
jTo terminal UE
iThe correction value of position distribution probability
(233) each terminal UE
iAll with its initial position coordinate P
i(x
i, y
i) with every other terminal to the correction value of its position distribution probability
Tire out and take advantage of amassing, as the position distribution probability after its k time iteration
Simultaneously, terminal UE
iAlso with the correction value of every other terminal to its position distribution probability
Tire out take advantage of long-pending, as after the k time iteration, terminal UE
iThe aided location distribution probability
(234) calculate each terminal UE earlier
iThe desired value of plane coordinates under the aided location distribution probability, i.e. the average of its a plurality of plane coordinatess, obtain the k time iteration after, this terminal UE
iPosition coordinates
And then after directly calculating the k time iteration, the approximate distance of each terminal room
Judge simultaneously whether iterations k reaches set point number, if then carry out subsequent step (235); Otherwise, return execution in step (232);
(235) each terminal UE to be measured
iThe final position distribution probability
Calculate this terminal location coordinate to be measured at final position distribution probability P '
i(x
i, y
i) under desired value, promptly the average of its a plurality of plane coordinatess is exactly the final position estimated value of this terminal to be measured
(236) base station is with each terminal UE to be measured
iThe final position estimated value send to each terminal to be measured.
9. method according to claim 5 is characterized in that: described step (3) comprises following concrete operations content:
(31) produce new terminal data vector to be measured or drive test terminal data vector in the network, just begin to upgrade position measurement sample storehouse: if in the position measurement sample storehouse memory space of terminal database to be measured less than, just store with terminal data vector to be measured that should be new is direct; Otherwise, in the alternative terminal database to be measured of terminal data vector to be measured that just will be new memory time data vector at most; The update method of drive test terminal data vector is identical with terminal data vector to be measured, makes limited terminal to be measured and the drive test terminal data vector that the time that stores all the time in the position measurement sample storehouse is nearest like this;
(32) after the renewal in sample storehouse is measured in the completing place, just,, finish the renewal of locus code book by clustering method according to drive test terminal and terminal data vector to be measured in the position measurement sample storehouse after upgrading.
10. according to claim 6 or 9 described methods, it is characterized in that: described step (32) comprises following concrete operations content:
(321) data vector that will upgrade in the preceding locus code book is put initial value as cluster;
(322), calculate the cluster point of Euclidean distance minimum equivalent respectively, and it is belonged to this cluster point with it to each the drive test terminal in the position measurement sample storehouse and the data vector of terminal to be measured; Feasible cluster group of data vector formation who belongs to the terminal to be measured and the drive test terminal of same cluster point, promptly each cluster point is all corresponding with a cluster faciation; Each data volume outline when calculating equivalent Euclidean distance is unified;
(323) calculate the average of every measurement data of the data vector of terminal to be measured among each cluster group and drive test terminal, obtain the cluster point after this cluster iteration;
(324) calculate and the mean square error of judging the cluster point before cluster point and its cluster iteration after this cluster iteration whether less than setting threshold, if, then deposit this cluster point data vector in the locus code book, finish the renewal of locus code book; Otherwise, return execution in step (322).
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